# Send ScholarGraph to your agent Use the source page and any available docs to guide the install because the item is currently unstable or timing out. ## Fast path - Open the source page via Review source status. - If you can obtain the package, extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the source page and extracted files. ## Suggested prompts ### New install ```text I tried to install a skill package from Yavira, but the item is currently unstable or timing out. Inspect the source page and any extracted docs, then tell me what you can confirm and any manual steps still required. ``` ### Upgrade existing ```text I tried to upgrade a skill package from Yavira, but the item is currently unstable or timing out. Compare the source page and any extracted docs with my current installation, then summarize what changed and what manual follow-up I still need. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "scholargraph", "name": "ScholarGraph", "source": "tencent", "type": "skill", "category": "开发工具", "sourceUrl": "https://clawhub.ai/Josephyb97/scholargraph", "canonicalUrl": "https://clawhub.ai/Josephyb97/scholargraph", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/scholargraph", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=scholargraph", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "CHANGELOG.md", "cli.ts", "concept-extractor/scripts/extract.ts", "concept-extractor/scripts/types.ts", "concept-learner/scripts/learn.ts", "concept-learner/scripts/types.ts" ], "downloadMode": "manual_only", "sourceHealth": { "source": "tencent", "slug": "scholargraph", "status": "unstable", "reason": "timeout", "recommendedAction": "retry_later", "checkedAt": "2026-05-08T12:13:10.267Z", "expiresAt": "2026-05-09T00:13:10.267Z", "httpStatus": null, "finalUrl": null, "contentType": null, "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=scholargraph", "error": "Timed out after 5000ms", "slug": "scholargraph" }, "scope": "item", "summary": "Item is unstable.", "detail": "This item is timing out or returning errors right now. Review the source page and try again later.", "primaryActionLabel": "Review source status", "primaryActionHref": "https://clawhub.ai/Josephyb97/scholargraph" }, "validation": { "installChecklist": [ "Wait for the source to recover or retry later.", "Review SKILL.md only after the download returns a real package.", "Treat this source as transient until the upstream errors clear." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/scholargraph", "downloadUrl": "https://openagent3.xyz/downloads/scholargraph", "agentUrl": "https://openagent3.xyz/skills/scholargraph/agent", "manifestUrl": "https://openagent3.xyz/skills/scholargraph/agent.json", "briefUrl": "https://openagent3.xyz/skills/scholargraph/agent.md" } } ``` ## Documentation ### Overview ScholarGraph is a comprehensive academic literature intelligence toolkit that helps researchers efficiently search, analyze, and manage academic papers using AI-powered tools. Features 11 academic search sources with intelligent domain-based source selection and PDF download capabilities. ### Security & Privacy This skill operates with the following permissions: Network Access: Queries academic APIs (arXiv, Semantic Scholar, OpenAlex, PubMed, CrossRef, DBLP, IEEE, CORE, Google Scholar, Unpaywall) and web search services File System: Reads/writes configuration files, downloads PDFs, stores knowledge graphs in SQLite database (data/knowledge-graphs.db) LLM Integration: Sends custom system prompts to AI providers for structured JSON output (concept extraction, paper analysis, etc.) Optional Python: PDF figure extraction (pymupdf) and PPT export (python-pptx) require Python 3.8+ Data Storage: All data is stored locally. No telemetry or analytics are collected. API Keys: Optional API keys are only used for their respective services and are never transmitted elsewhere. Source Code: Open source under MIT license at https://github.com/Josephyb97/ScholarGraph ### Core Modules (6) Literature Search - Multi-source academic paper discovery (11 sources) Free sources: arXiv, Semantic Scholar, OpenAlex (250M+), PubMed (biomedical), CrossRef (150M+ DOI), DBLP (CS), Web Search API-key sources: IEEE Xplore, CORE, Google Scholar (SerpAPI), Unpaywall (OA PDF) Adapter-based plugin architecture for easy extension Complementary search strategy with auto domain detection (biomedical/cs/engineering/physics) Priority-based source selection per domain Query expansion for better search results PDF download with multi-strategy URL resolution Concept Learner - Rapid knowledge framework construction Generate structured learning cards Include code examples and related papers Support beginner/intermediate/advanced depth levels Knowledge Gap Detector - Proactive blind spot identification Analyze knowledge coverage in specific domains Identify critical, recommended, and optional gaps Provide learning recommendations and time estimates Progress Tracker - Real-time field monitoring Track research topics and keywords Generate daily/weekly/monthly reports Monitor trending papers and topics Paper Analyzer - Deep paper analysis Extract key contributions and insights Support quick/standard/deep analysis modes Generate structured analysis reports Knowledge Graph Builder - Concept relationship visualization Build interactive knowledge graphs Support Mermaid and JSON output formats Find learning paths between concepts SQLite-based persistent storage Bidirectional concept-paper indexing ### Advanced Features (9) Review Detector - Automatic review paper identification Multi-dimensional scoring (title 30% + citations 25% + abstract 25% + AI 20%) Chinese and English keyword support Confidence-based filtering with user confirmation Concept Extractor - Extract concepts from review papers AI-powered extraction of 15-30 core concepts Four-level categorization (foundation/core/advanced/application) Importance scoring and relationship identification Cross-review deduplication and merging Review-to-Graph Workflow - End-to-end pipeline Search reviews -> Detect -> Confirm -> Analyze -> Extract concepts Build knowledge graph -> Enrich with key papers -> Index -> Store Interactive or automatic confirmation mode Knowledge Graph Query - Bidirectional literature indexing Concept -> papers: find papers related to a concept Paper -> concepts: find concepts covered by a paper Paper recommendations based on multiple concepts SQLite-optimized high-performance queries Compare Concepts - Compare two concepts Identify similarities and differences Provide use case recommendations Compare Papers - Compare multiple papers Find common themes and differences Generate synthesis analysis Critique - Critical paper analysis Identify strengths and weaknesses Find research gaps and improvement suggestions Support custom focus areas Learning Path - Find optimal learning paths Discover paths between concepts Generate topological learning order Visualize with Mermaid diagrams Graph Management - Manage persistent knowledge graphs List all saved graphs View graph statistics Export graphs to JSON Visualize with Mermaid Paper Visualization - Interactive paper presentation Convert paper analysis to HTML slide presentations Academic dark/light themes with responsive typography Keyboard/touch/scroll navigation, edit mode (E key) PDF figure extraction (pymupdf) and PPT export (python-pptx) 8+ slides: title, abstract, key points, methodology, experiments, contributions, limitations, references Interactive Knowledge Graph - D3.js force-directed visualization Convert knowledge graphs to interactive HTML with D3.js v7 Node size reflects paper count, edge thickness reflects concept tightness Zoom/pan, node dragging, click-to-detail panel, search, legend Paper preview bridge: click "View Presentation" to open paper slides in new tab Category colors: foundation=#4FC3F7, core=#FFB74D, advanced=#CE93D8, application=#81C784 ### Technical Features 11 Academic Search Sources: arXiv, Semantic Scholar, OpenAlex, PubMed, CrossRef, DBLP, IEEE Xplore, CORE, Google Scholar, Unpaywall, Web Search Complementary Search Strategy: Auto-detects query domain and selects optimal source combination Adapter Pattern: Plugin-based search source architecture for easy extension PDF Download: Multi-strategy URL resolution (direct, Unpaywall, OpenAlex OA, CORE) Multi-AI Provider Support: 15+ AI providers including OpenAI, Anthropic, DeepSeek, Qwen, Zhipu AI, etc. SQLite Persistence: Knowledge graphs stored in SQLite database via bun:sqlite Bidirectional Indexing: Concept-paper and paper-concept bidirectional query support Rate Limiting: Per-source rate limiting with automatic retry and delay Interactive HTML Output: Paper slide presentations, D3.js knowledge graph visualizations Multiple Output Formats: Markdown, JSON, Mermaid, HTML, PPTX TypeScript + Bun: Fast and type-safe runtime CLI + API: Both command-line and programmatic interfaces ### Installation # Clone repository git clone https://github.com/Josephyb97/ScholarGraph.git cd ScholarGraph # Install dependencies bun install # Initialize configuration bun run cli.ts config init ### Configuration Set up your AI provider: # Using OpenAI export AI_PROVIDER=openai export OPENAI_API_KEY="your-api-key" # Using DeepSeek export AI_PROVIDER=deepseek export DEEPSEEK_API_KEY="your-api-key" # Using Qwen (通义千问) export AI_PROVIDER=qwen export QWEN_API_KEY="your-api-key" ### Academic Source API Keys (optional, expand search coverage) export NCBI_API_KEY="your-key" # PubMed high-speed access (10 req/s) export IEEE_API_KEY="your-key" # IEEE Xplore engineering papers export CORE_API_KEY="your-key" # CORE open access full text export UNPAYWALL_EMAIL="your@email.com" # Unpaywall OA PDF resolver export CROSSREF_MAILTO="your@email.com" # CrossRef polite pool (higher rate) export SERPAPI_KEY="your-key" # Google Scholar (via SerpAPI) export SERPER_API_KEY="your-key" # Web search via Serper ### Search Literature # Auto-select best sources based on query domain lit search "transformer attention" --limit 20 # Specify domain for optimized source selection lit search "CRISPR gene editing" --domain biomedical # Use specific sources (comma-separated) lit search "deep learning" --source semantic_scholar,arxiv,openalex --sort citations # Search and download PDFs lit search "attention is all you need" --download --limit 3 ### Download PDFs # Search and download PDFs lit download "transformer" --limit 5 --output ./papers ### Learn Concepts lit learn "BERT" --depth advanced --papers --code --output bert-card.md ### Detect Knowledge Gaps lit detect --domain "Deep Learning" --known "CNN,RNN" --output gaps.md ### Analyze Papers lit analyze "https://arxiv.org/abs/1706.03762" --mode deep --output analysis.md ### Build Knowledge Graph lit graph transformer attention BERT GPT --format mermaid --output graph.md ### Compare Concepts lit compare concepts CNN RNN --output comparison.md ### Compare Papers lit compare papers "url1" "url2" "url3" --output comparison.md ### Critical Analysis lit critique "paper-url" --focus "novelty,scalability" --output critique.md ### Find Learning Path lit path "Machine Learning" "Deep Learning" --concepts "Neural Networks" --output path.md ### Search Review Papers lit review-search "attention mechanism" --limit 10 ### Build Knowledge Graph from Reviews # From search query (interactive mode) lit review-graph "deep learning" --output dl-graph --enrich # From specific URL lit review-graph "https://arxiv.org/abs/xxxx" --output my-graph --enrich # Auto-confirm mode (non-interactive) lit review-graph "transformer" --output tf-graph --enrich --auto-confirm ### Query Knowledge Graph # Find papers by concept lit query concept "transformer" --graph dl-graph --limit 20 # Find concepts by paper lit query paper "https://arxiv.org/abs/1706.03762" --graph dl-graph ### Manage Knowledge Graphs # List all graphs lit graph-list # View graph statistics lit graph-stats dl-graph # Visualize graph lit graph-viz dl-graph --format mermaid --output graph.md # Export graph lit graph-export dl-graph --output dl-graph.json ### Paper Visualization # Generate interactive HTML presentation lit paper-viz "https://arxiv.org/abs/1706.03762" --output attention.html # With theme and PPT export lit paper-viz "https://arxiv.org/abs/1706.03762" --mode deep --theme academic-light --ppt # Manually provide figures lit paper-viz "https://example.com/paper" --figures ./my-figures ### Interactive Knowledge Graph # Generate interactive D3.js graph from existing knowledge graph lit graph-interactive dl-graph --output dl-interactive.html # Without paper data (lighter weight) lit graph-interactive my-graph --no-paper-viz ### 1. Quick Field Onboarding Learn core concepts Detect prerequisite gaps Build knowledge graph Plan learning path ### 2. Deep Paper Understanding Analyze paper in depth Perform critical analysis Learn new concepts from paper Compare with related papers ### 3. Research Progress Tracking Monitor research topics Track latest papers Generate progress reports ### 4. Concept Comparison Compare technical approaches Evaluate different models Build comparison graphs ### 5. Review-Driven Knowledge Building Search and identify review papers Extract concepts from reviews Build persistent knowledge graphs Query concept-paper relationships ### 6. Paper Visualization & Graph Exploration Analyze paper and generate interactive HTML presentation Build knowledge graph from reviews Generate interactive D3.js graph with paper preview Click nodes to view paper details and open presentations ### Project Structure ScholarGraph/ ├── cli.ts # Unified CLI entry ├── config.ts # Configuration management ├── README.md # Project documentation ├── CHANGELOG.md # Version history ├── SKILL.md # This file │ ├── shared/ # Shared modules │ ├── ai-provider.ts # AI provider abstraction │ ├── types.ts # Type definitions │ ├── validators.ts # Parameter validation │ ├── errors.ts # Error handling │ └── utils.ts # Utility functions │ ├── literature-search/ # Literature search module │ └── scripts/ │ ├── search.ts # Search engine core │ ├── types.ts # Type definitions │ ├── query-expander.ts # Query expansion │ ├── search-strategy.ts # Complementary search strategy │ ├── pdf-downloader.ts # PDF download module │ └── adapters/ # Search source adapters │ ├── base.ts # Adapter interface & base class │ ├── registry.ts # Adapter registry │ ├── index.ts # Barrel export │ ├── arxiv-adapter.ts │ ├── semantic-scholar-adapter.ts │ ├── web-adapter.ts │ ├── openalex-adapter.ts │ ├── pubmed-adapter.ts │ ├── crossref-adapter.ts │ ├── dblp-adapter.ts │ ├── ieee-adapter.ts │ ├── core-adapter.ts │ ├── unpaywall-adapter.ts │ └── google-scholar-adapter.ts │ ├── concept-learner/ # Concept learning module ├── knowledge-gap-detector/ # Gap detection module ├── progress-tracker/ # Progress tracking module ├── paper-analyzer/ # Paper analysis module │ ├── review-detector/ # Review paper identification │ └── scripts/ │ ├── detect.ts # Multi-dimensional scoring │ └── types.ts │ ├── concept-extractor/ # Concept extraction from reviews │ └── scripts/ │ ├── extract.ts # AI-powered extraction │ └── types.ts │ ├── knowledge-graph/ # Knowledge graph module │ └── scripts/ │ ├── graph.ts # Graph building core │ ├── indexer.ts # Bidirectional indexing │ ├── storage.ts # SQLite persistence │ └── enricher.ts # Key paper association │ ├── paper-viz/ # Paper visualization │ └── scripts/ │ ├── types.ts # Presentation data interfaces │ ├── slide-builder.ts # PaperAnalysis → slides │ ├── html-generator.ts # Self-contained HTML generation │ ├── pdf-figure-extractor.ts # PDF figure extraction (pymupdf) │ └── ppt-exporter.ts # PPT export (python-pptx) │ ├── graph-viz/ # Interactive knowledge graph │ └── scripts/ │ ├── types.ts # D3 graph data interfaces │ ├── graph-data-adapter.ts # KnowledgeGraph → D3 data │ ├── html-generator.ts # Interactive HTML (D3.js v7) │ └── paper-viz-bridge.ts # Graph → paper presentation bridge │ ├── workflows/ # End-to-end workflows │ └── review-to-graph.ts # Review to graph pipeline │ ├── data/ # Data directory (auto-created) │ └── knowledge-graphs.db # SQLite database │ ├── downloads/ # PDF downloads (auto-created) │ └── pdfs/ │ └── metadata.json # Download index │ └── test/ # Tests and documentation ├── ADVANCED_FEATURES.md ├── TEST_RESULTS.md └── scripts/ ### International OpenAI Anthropic (Claude) Azure OpenAI Groq Together AI Ollama (local) ### China 通义千问 (Qwen/DashScope) DeepSeek 智谱 AI (GLM) MiniMax Moonshot (Kimi) 百川 AI (Baichuan) 零一万物 (Yi) 豆包 (Doubao) ### Markdown Reports Concept cards with definitions, components, history, applications Gap reports with analysis and recommendations Progress reports with trending topics Paper analyses with methods, experiments, contributions Comparison analyses with similarities and differences Critical analyses with strengths, weaknesses, and suggestions ### JSON Data Structured data for programmatic processing ### Mermaid Diagrams Interactive knowledge graphs and learning paths ### Interactive HTML Paper slide presentations with keyboard/scroll/touch navigation D3.js force-directed knowledge graph with zoom, search, and paper panel ### Requirements Bun 1.3+ or Node.js 18+ AI provider API key Internet connection for paper search Python 3.8+ (optional, for PDF figure extraction and PPT export) ### License MIT License ### Links GitHub: https://github.com/Josephyb97/ScholarGraph Issues: https://github.com/Josephyb97/ScholarGraph/issues Discussions: https://github.com/Josephyb97/ScholarGraph/discussions ### Version Current version: 1.0.0 ### Author ScholarGraph Team Design Inspirations: frontend-slides - Paper slide presentation design reference Argo Scholar - Interactive knowledge graph design reference For detailed documentation, see README.md For advanced features, see test/ADVANCED_FEATURES.md For test results, see test/TEST_RESULTS.md ## Trust - Source: tencent - Verification: Indexed source record - Publisher: Josephyb97 - Version: 1.4.3 ## Source health - Status: unstable - Item is unstable. - This item is timing out or returning errors right now. Review the source page and try again later. - Health scope: item - Reason: timeout - Checked at: 2026-05-08T12:13:10.267Z - Expires at: 2026-05-09T00:13:10.267Z - Recommended action: Review source status ## Links - [Detail page](https://openagent3.xyz/skills/scholargraph) - [Send to Agent page](https://openagent3.xyz/skills/scholargraph/agent) - [JSON manifest](https://openagent3.xyz/skills/scholargraph/agent.json) - [Markdown brief](https://openagent3.xyz/skills/scholargraph/agent.md) - [Download page](https://openagent3.xyz/downloads/scholargraph)